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cs.CL2025
Avoiding Knowledge Edit Skipping in Multi-hop Question Answering with Guided Decomposition
Yi Liu, Xiangrong Zhu, Xiangyu Liu +2
In a rapidly evolving world where information updates swiftly, knowledge in large language models (LLMs) becomes outdated quickly. Retraining LLMs is not a cost-effective option, m…
cs.CL2025
Knowledge Graph-Guided Retrieval Augmented Generation
Xiangrong Zhu, Yuexiang Xie, Yi Liu +2
Retrieval-augmented generation (RAG) has emerged as a promising technology for addressing hallucination issues in the responses generated by large language models (LLMs). Existing…
cs.CL2024
Multi-Aspect Controllable Text Generation with Disentangled Counterfactual Augmentation
Yi Liu, Xiangyu Liu, Xiangrong Zhu +1
Multi-aspect controllable text generation aims to control the generated texts in attributes from multiple aspects (e.g., "positive" from sentiment and "sport" from topic). For ease…